SlideShare une entreprise Scribd logo
1  sur  19
Data Collection
At the end of this lesson, the student should be able to:


1. recognize the importance of data gathering;



2. distinguish primary from secondary data sources;



3. define population and sampling;



4. define census and sample;



5. identify the various data collection techniques and sources
of data;



6. describe the various instruments for data gathering;



7. cite the advantages of the use of such instruments;



8. recognize the limitations of certain research instruments;
1.

Primary sources of data - are those that

provide information that are collected for the first
time as part of a research project.

- are tangible
materials that provide a description of a historical
event and were produced shortly after the event
took place.
Example: Newspaper stories, personal letters, public
documents, eyewitness, verbal accounts, court
decisions, and personal diaries

-
2. Secondary sources - are those that provide
data which have been collected previously and
reported by some individual other than the present
researcher
- borrowed knowledge from other
sources.
- refers to the processes whereby a sub-group is
picked out from a larger group and then use this subgroup as a basis for making judgments about the
larger group.

- called a sample
- referred to as population


Population - is a
whether individuals, animals, objects, or events that
conform to specific criteria and to which one intend to
generalize the results of the research (McMillan, 1998; Wood
& Haber, 1998).



A census is a study that collects data from all members of
the population.


Target population is the group or set of items or
individuals from which or about which
representative information is originally desired.



Sampling population is the population from
which a sample is actually drawn.



A sample is a set of elements, or a single
element, from which data are obtained


Researchers generally use sampling because of
budget, time, and manpower constraints. Such constraints
prevent them from undertaking a complete study of the
total target population.
1. Reduced cost
2. Greater speed
3. Greater scope
4. Greater accuracy


A probability sampling method - is any method of sampling
that utilizes some form of random selection.



In order to have a random selection method, you must set up
some process or procedure that assures that the different
units in your population have equal probabilities of being
chosen.


1. Simple random sampling - is a process of selecting a sample from a
set of all sampling units, giving each unit in the frame an equal chance of
being included in the sample.

Two ways of randomly selecting samples:
- lottery method
- using table of random numbers - contains columns of digits that have been
mechanically generated, usually by a computer, to assume a random order.


2. Systematic sampling - refers to the process of selecting every kth
sampling unit of the population after the first sampling unit is selected at
random from the first k sampling units


3. Stratified sampling - involves dividing the population into two or
more strata and then taking either a simple random (stratified random
sampling) or a systematic sample (stratified systematic sampling) from
each stratum.



4. Cluster sampling - is a method of selecting a sample of distinct
groups of clusters of smaller units called elements.
- A cluster refers to any intact group of similar

characteristics.


5. Multistage sampling -is a complex form of cluster sampling.
Cluster sampling is a type of sampling which involves dividing the
population into groups (or clusters).

- Using all the sample elements in all the selected
clusters may be prohibitively expensive or not necessary.

- the researcher randomly selects elements from
each cluster.
Two stages of Multistage sampling


First stage - Constructing the clusters



Second stage - Deciding what elements within the cluster
to use.

The technique is used frequently when a complete list of
all members of the population does not exist and is
inappropriate.


Despite the accepted superiority of probability sampling
designs, the researcher is sometimes faced with the
problem of whether he would use nonprobability
sampling or not.



This is especially true when probability sampling
becomes expensive or when precise representatives are
not necessary.
Types of Nonprobability Sampling:
 1.

Convenience sampling

- is selecting sampling units that are easily
(conveniently) available to the researcher.

- It is used in exploratory research where the
researcher is interested in getting an inexpensive approximation of the truth.

- used during preliminary research efforts to get a
gross estimate of the results, without incurring the cost or time required to
select a random sample.

 2.

Judgment sampling or purposive sampling

- is selecting
units to be observed on the basis of our judgment about which one will be
useful or representative. The researcher selects the sample based on
judgment.
 3.

Quota sampling - is selecting samples on the basis of

pre-specified characteristics, so that the total sample will
have the same distribution of characteristics as assumed to
exist in the population being studied. The researcher first
identifies the stratums and their proportions as they are
represented in the population.
 4.

Dimensional sampling - is a multi-dimensional

extension of quota sampling.
- In this sampling
procedure, instead of a large size, a small size is selected. It is
emphasized that all areas of interest should cover at least one case.


5. Voluntary sampling - is a special type of sampling in which



6. Snowball sampling or sometimes called networking
sampling - researcher first identifies few individuals for the sample





subjects/cases are informed about the subject matter willingly or
voluntarily participate in the study. This sampling is useful especially if
one dealing with information on sensitive or delicate issues.

and uses them as informants. On the basis of their information, the
researcher collects the name of more persons bearing similar
characteristics.
Useful when one wants to consider possible respondents who are not
normally visible.
Used when the desired sample characteristic is rare
For example, study of drug addicts in a university, or a study of socioeconomic conditions of teacher-retirees, or a study of patients with AIDS


1. Questionnaire - is often referred to as a “lazy man’s way of gaining
information”. It is also said that it is the most used and abused of data-gathering
devices. However, a carefully prepared questionnaire can yield better data.



2. Interview Method - is one of the data-gathering techniques in research. It
is defined as a face-to-face interaction between two persons. The one who asks
questions is called the interviewer and the one who supplies the information
asked for is called the interviewee or respondent.



scheduled-structured interview,



nonscheduled-structured interview



nonscheduled interview


3. Opinionnaire - is an instrument that attempts to obtain the measured
attitude or belief of an individual. The opinionnaire is usually used to infer
attitude-expressed opinion of an individual.



This may be done by: directly asking how one feels about the subject



In asking an individual directly how one feels about the subject, we may use
either semantic differential scale or the Likert scale.



4. Projective methods - involve some sort of imaginative activity on the
part of the individual in interpreting ambiguous stimuli.



Projective methods were first used by psychologists wherein tests administered
provide a comprehensive picture of an individual’s personality
structure, emotional needs, conflicts and other feelings. In these
tests, responses of the individual are not taken on face value but are based on
some pre-established psychological conceptualization. The use of
pictures, verbal techniques, and play techniques are mostly used in
projective methods
5. Observation - is a process whereby the
researcher watches the research situation.
 This

data-collecting technique is mostly used when the
respondents are unwillingly to express themselves
verbally.

 Observation

may be natural or contrived; disguised or
undisguised; structured or unstructured; direct or
indirect.

Contenu connexe

Tendances

SAMPLING AND SAMPLING ERRORS
SAMPLING AND SAMPLING ERRORSSAMPLING AND SAMPLING ERRORS
SAMPLING AND SAMPLING ERRORSrambhu21
 
data collection primary secondary methods
data collection primary secondary methodsdata collection primary secondary methods
data collection primary secondary methodsAlen philip
 
8. validity and reliability of research instruments
8. validity and reliability of research instruments8. validity and reliability of research instruments
8. validity and reliability of research instrumentsRazif Shahril
 
Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...
Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...
Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...Bikash Sapkota
 
Sampling and Sample Types
Sampling  and Sample TypesSampling  and Sample Types
Sampling and Sample TypesDr. Sunil Kumar
 
Sampling Methods & Sampling Error PPT - For Seminar
Sampling Methods & Sampling Error PPT - For Seminar Sampling Methods & Sampling Error PPT - For Seminar
Sampling Methods & Sampling Error PPT - For Seminar Amal G
 
Sampling techniques and types
Sampling techniques and typesSampling techniques and types
Sampling techniques and typesNITISH SADOTRA
 
Questionnaire Method of Data Collection
Questionnaire Method of Data CollectionQuestionnaire Method of Data Collection
Questionnaire Method of Data CollectionDr. Amitabh Mishra
 
050 sampling theory
050 sampling theory050 sampling theory
050 sampling theoryRaj Teotia
 
Method for data collection 2
Method for data collection 2Method for data collection 2
Method for data collection 2PK Joshua
 
Simple random sampling
Simple random samplingSimple random sampling
Simple random samplingsuncil0071
 
RESEARCH METHOD - SAMPLING
RESEARCH METHOD - SAMPLINGRESEARCH METHOD - SAMPLING
RESEARCH METHOD - SAMPLINGHafizah Hajimia
 
Methods of Data Collection, Sampling Techniques and Methods in Presenting Data
Methods of Data Collection, Sampling Techniques and Methods in Presenting DataMethods of Data Collection, Sampling Techniques and Methods in Presenting Data
Methods of Data Collection, Sampling Techniques and Methods in Presenting DataRG Luis Vincent Gonzaga
 
Statistics in research
Statistics in researchStatistics in research
Statistics in researchBalaji P
 
Sampling methods 16
Sampling methods   16Sampling methods   16
Sampling methods 16Raj Selvam
 
Inferential statistics.ppt
Inferential statistics.pptInferential statistics.ppt
Inferential statistics.pptNursing Path
 

Tendances (20)

SAMPLING AND SAMPLING ERRORS
SAMPLING AND SAMPLING ERRORSSAMPLING AND SAMPLING ERRORS
SAMPLING AND SAMPLING ERRORS
 
data collection primary secondary methods
data collection primary secondary methodsdata collection primary secondary methods
data collection primary secondary methods
 
8. validity and reliability of research instruments
8. validity and reliability of research instruments8. validity and reliability of research instruments
8. validity and reliability of research instruments
 
Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...
Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...
Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...
 
Sampling and Sample Types
Sampling  and Sample TypesSampling  and Sample Types
Sampling and Sample Types
 
Sampling Methods & Sampling Error PPT - For Seminar
Sampling Methods & Sampling Error PPT - For Seminar Sampling Methods & Sampling Error PPT - For Seminar
Sampling Methods & Sampling Error PPT - For Seminar
 
Sampling techniques and types
Sampling techniques and typesSampling techniques and types
Sampling techniques and types
 
Questionnaire Method of Data Collection
Questionnaire Method of Data CollectionQuestionnaire Method of Data Collection
Questionnaire Method of Data Collection
 
050 sampling theory
050 sampling theory050 sampling theory
050 sampling theory
 
Method for data collection 2
Method for data collection 2Method for data collection 2
Method for data collection 2
 
Simple random sampling
Simple random samplingSimple random sampling
Simple random sampling
 
RESEARCH METHOD - SAMPLING
RESEARCH METHOD - SAMPLINGRESEARCH METHOD - SAMPLING
RESEARCH METHOD - SAMPLING
 
Methods of Data Collection, Sampling Techniques and Methods in Presenting Data
Methods of Data Collection, Sampling Techniques and Methods in Presenting DataMethods of Data Collection, Sampling Techniques and Methods in Presenting Data
Methods of Data Collection, Sampling Techniques and Methods in Presenting Data
 
Statistics in research
Statistics in researchStatistics in research
Statistics in research
 
sampling ppt
sampling pptsampling ppt
sampling ppt
 
Descriptive Method
Descriptive MethodDescriptive Method
Descriptive Method
 
Sampling in research
 Sampling in research Sampling in research
Sampling in research
 
Sampling methods 16
Sampling methods   16Sampling methods   16
Sampling methods 16
 
Inferential statistics.ppt
Inferential statistics.pptInferential statistics.ppt
Inferential statistics.ppt
 
SAMPLING
SAMPLINGSAMPLING
SAMPLING
 

Similaire à Data collection-statistics

Similaire à Data collection-statistics (20)

Research feb22
Research  feb22Research  feb22
Research feb22
 
Project Monitorig and Evaluation_Data Collection Methods.pptx
Project Monitorig and Evaluation_Data Collection Methods.pptxProject Monitorig and Evaluation_Data Collection Methods.pptx
Project Monitorig and Evaluation_Data Collection Methods.pptx
 
Theory of sampling
Theory of samplingTheory of sampling
Theory of sampling
 
methodology in research
  methodology in research  methodology in research
methodology in research
 
Sampling , Advantages limitations
Sampling , Advantages limitationsSampling , Advantages limitations
Sampling , Advantages limitations
 
POPULATION, SAMPLE AND SAMPLING TECHNIQUE.pptx
POPULATION, SAMPLE AND SAMPLING TECHNIQUE.pptxPOPULATION, SAMPLE AND SAMPLING TECHNIQUE.pptx
POPULATION, SAMPLE AND SAMPLING TECHNIQUE.pptx
 
Mm23
Mm23Mm23
Mm23
 
Data Collection
Data CollectionData Collection
Data Collection
 
Mm22
Mm22Mm22
Mm22
 
Descriptive
DescriptiveDescriptive
Descriptive
 
chapter4-understandingdataandwaystosystematicallycollectdata-170809052400.pptx
chapter4-understandingdataandwaystosystematicallycollectdata-170809052400.pptxchapter4-understandingdataandwaystosystematicallycollectdata-170809052400.pptx
chapter4-understandingdataandwaystosystematicallycollectdata-170809052400.pptx
 
Research methodology ppt
Research methodology pptResearch methodology ppt
Research methodology ppt
 
Descriptive Method
Descriptive MethodDescriptive Method
Descriptive Method
 
Chapter 4 Understanding Data and Ways to Systematically Collect Data
Chapter 4   Understanding Data and Ways to Systematically Collect DataChapter 4   Understanding Data and Ways to Systematically Collect Data
Chapter 4 Understanding Data and Ways to Systematically Collect Data
 
Case study method
Case study methodCase study method
Case study method
 
Sampling methods.pptx
Sampling methods.pptxSampling methods.pptx
Sampling methods.pptx
 
Methods of sampling
Methods of sampling Methods of sampling
Methods of sampling
 
research methods
research methodsresearch methods
research methods
 
Non-Probability Sampling
Non-Probability Sampling Non-Probability Sampling
Non-Probability Sampling
 
Sampling research method
Sampling research methodSampling research method
Sampling research method
 

Plus de Roi Fernandez

Plus de Roi Fernandez (20)

History of computer
History of computerHistory of computer
History of computer
 
Other european nations
 Other european nations Other european nations
Other european nations
 
Kitchen utensils ppt
Kitchen utensils pptKitchen utensils ppt
Kitchen utensils ppt
 
India
IndiaIndia
India
 
Geographic setting of india
Geographic setting of indiaGeographic setting of india
Geographic setting of india
 
Early Civilizations
Early CivilizationsEarly Civilizations
Early Civilizations
 
Stages of man
Stages of manStages of man
Stages of man
 
The early men 3
The early men 3The early men 3
The early men 3
 
Civilization of smaller states
Civilization of smaller statesCivilization of smaller states
Civilization of smaller states
 
Continents
 Continents Continents
Continents
 
Pehm music unit 1 lesson 3
 Pehm music unit 1 lesson 3 Pehm music unit 1 lesson 3
Pehm music unit 1 lesson 3
 
Alternative peh mreport
Alternative peh mreportAlternative peh mreport
Alternative peh mreport
 
Topaz research
Topaz researchTopaz research
Topaz research
 
Smooth er
Smooth erSmooth er
Smooth er
 
Smooth Endoplasmic Reticulum
 Smooth Endoplasmic Reticulum Smooth Endoplasmic Reticulum
Smooth Endoplasmic Reticulum
 
Lesson 2
Lesson 2Lesson 2
Lesson 2
 
Human Geography
 Human Geography Human Geography
Human Geography
 
Landforms and Waterforms
 Landforms and Waterforms Landforms and Waterforms
Landforms and Waterforms
 
Geographical Quiz
Geographical QuizGeographical Quiz
Geographical Quiz
 
5 themes of geography
 5 themes of geography 5 themes of geography
5 themes of geography
 

Dernier

Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxLoriGlavin3
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxLoriGlavin3
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfLoriGlavin3
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxBkGupta21
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .Alan Dix
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteDianaGray10
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.Curtis Poe
 

Dernier (20)

Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptx
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdf
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptx
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test Suite
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.
 

Data collection-statistics

  • 2. At the end of this lesson, the student should be able to:  1. recognize the importance of data gathering;  2. distinguish primary from secondary data sources;  3. define population and sampling;  4. define census and sample;  5. identify the various data collection techniques and sources of data;  6. describe the various instruments for data gathering;  7. cite the advantages of the use of such instruments;  8. recognize the limitations of certain research instruments;
  • 3. 1. Primary sources of data - are those that provide information that are collected for the first time as part of a research project. - are tangible materials that provide a description of a historical event and were produced shortly after the event took place. Example: Newspaper stories, personal letters, public documents, eyewitness, verbal accounts, court decisions, and personal diaries -
  • 4. 2. Secondary sources - are those that provide data which have been collected previously and reported by some individual other than the present researcher - borrowed knowledge from other sources.
  • 5. - refers to the processes whereby a sub-group is picked out from a larger group and then use this subgroup as a basis for making judgments about the larger group. - called a sample - referred to as population
  • 6.  Population - is a whether individuals, animals, objects, or events that conform to specific criteria and to which one intend to generalize the results of the research (McMillan, 1998; Wood & Haber, 1998).  A census is a study that collects data from all members of the population.
  • 7.  Target population is the group or set of items or individuals from which or about which representative information is originally desired.  Sampling population is the population from which a sample is actually drawn.  A sample is a set of elements, or a single element, from which data are obtained
  • 8.  Researchers generally use sampling because of budget, time, and manpower constraints. Such constraints prevent them from undertaking a complete study of the total target population. 1. Reduced cost 2. Greater speed 3. Greater scope 4. Greater accuracy
  • 9.  A probability sampling method - is any method of sampling that utilizes some form of random selection.  In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen.
  • 10.  1. Simple random sampling - is a process of selecting a sample from a set of all sampling units, giving each unit in the frame an equal chance of being included in the sample. Two ways of randomly selecting samples: - lottery method - using table of random numbers - contains columns of digits that have been mechanically generated, usually by a computer, to assume a random order.  2. Systematic sampling - refers to the process of selecting every kth sampling unit of the population after the first sampling unit is selected at random from the first k sampling units
  • 11.  3. Stratified sampling - involves dividing the population into two or more strata and then taking either a simple random (stratified random sampling) or a systematic sample (stratified systematic sampling) from each stratum.  4. Cluster sampling - is a method of selecting a sample of distinct groups of clusters of smaller units called elements. - A cluster refers to any intact group of similar characteristics.  5. Multistage sampling -is a complex form of cluster sampling. Cluster sampling is a type of sampling which involves dividing the population into groups (or clusters). - Using all the sample elements in all the selected clusters may be prohibitively expensive or not necessary. - the researcher randomly selects elements from each cluster.
  • 12. Two stages of Multistage sampling  First stage - Constructing the clusters  Second stage - Deciding what elements within the cluster to use. The technique is used frequently when a complete list of all members of the population does not exist and is inappropriate.
  • 13.  Despite the accepted superiority of probability sampling designs, the researcher is sometimes faced with the problem of whether he would use nonprobability sampling or not.  This is especially true when probability sampling becomes expensive or when precise representatives are not necessary.
  • 14. Types of Nonprobability Sampling:  1. Convenience sampling - is selecting sampling units that are easily (conveniently) available to the researcher. - It is used in exploratory research where the researcher is interested in getting an inexpensive approximation of the truth. - used during preliminary research efforts to get a gross estimate of the results, without incurring the cost or time required to select a random sample.  2. Judgment sampling or purposive sampling - is selecting units to be observed on the basis of our judgment about which one will be useful or representative. The researcher selects the sample based on judgment.
  • 15.  3. Quota sampling - is selecting samples on the basis of pre-specified characteristics, so that the total sample will have the same distribution of characteristics as assumed to exist in the population being studied. The researcher first identifies the stratums and their proportions as they are represented in the population.  4. Dimensional sampling - is a multi-dimensional extension of quota sampling. - In this sampling procedure, instead of a large size, a small size is selected. It is emphasized that all areas of interest should cover at least one case.
  • 16.  5. Voluntary sampling - is a special type of sampling in which  6. Snowball sampling or sometimes called networking sampling - researcher first identifies few individuals for the sample    subjects/cases are informed about the subject matter willingly or voluntarily participate in the study. This sampling is useful especially if one dealing with information on sensitive or delicate issues. and uses them as informants. On the basis of their information, the researcher collects the name of more persons bearing similar characteristics. Useful when one wants to consider possible respondents who are not normally visible. Used when the desired sample characteristic is rare For example, study of drug addicts in a university, or a study of socioeconomic conditions of teacher-retirees, or a study of patients with AIDS
  • 17.  1. Questionnaire - is often referred to as a “lazy man’s way of gaining information”. It is also said that it is the most used and abused of data-gathering devices. However, a carefully prepared questionnaire can yield better data.  2. Interview Method - is one of the data-gathering techniques in research. It is defined as a face-to-face interaction between two persons. The one who asks questions is called the interviewer and the one who supplies the information asked for is called the interviewee or respondent.  scheduled-structured interview,  nonscheduled-structured interview  nonscheduled interview
  • 18.  3. Opinionnaire - is an instrument that attempts to obtain the measured attitude or belief of an individual. The opinionnaire is usually used to infer attitude-expressed opinion of an individual.  This may be done by: directly asking how one feels about the subject  In asking an individual directly how one feels about the subject, we may use either semantic differential scale or the Likert scale.  4. Projective methods - involve some sort of imaginative activity on the part of the individual in interpreting ambiguous stimuli.  Projective methods were first used by psychologists wherein tests administered provide a comprehensive picture of an individual’s personality structure, emotional needs, conflicts and other feelings. In these tests, responses of the individual are not taken on face value but are based on some pre-established psychological conceptualization. The use of pictures, verbal techniques, and play techniques are mostly used in projective methods
  • 19. 5. Observation - is a process whereby the researcher watches the research situation.  This data-collecting technique is mostly used when the respondents are unwillingly to express themselves verbally.  Observation may be natural or contrived; disguised or undisguised; structured or unstructured; direct or indirect.